Scatterplot3d - an R package for visualizing multivariate data

By Uwe Ligges, M. Maechler. 2003

469 citations recorded by the source corpus.

Scatterplot3d is an R package for the visualization of multivariate data in a three dimensional space. R is a "language for data analysis and graphics". In this paper we discuss the features of the package. It is designed by exclusively making use of already existing functions of R and its graphics system and thus shows the extensibility of the R graphics system. Additionally some examples on generated and real world data are provided.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/9414e14875e7efdb420f4aa55e54651a88a94a9e

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Citations in the corpus

Mixed Effects Models and Extensions in Ecology with R (2009, background): “…(Bates and Sarkar, 2006), lmtest (Zeileis and Hothorn, 2002), MASS (Venables and Ripley, 2002), mgcv (Wood, 2004; 2006), ncf (Bjornstad, 2008), nlme (Pinheiro et al., 2008), pscl (Jackman, 2007), scatterplot3d (Ligges and Mächler, 2003), stats (R Development Core Team, 2008), and VGAM (Yee, 2007).”
Enjoy the Joy of Copulas: With a Package copula (2007, methodology): “In the sequel, all R code demonstration assumes that the package has been loaded: R> library("copula") The required packages mvtnorm (Genz, Bretz, and Hothorn 2005), sn (Azzalini 2006), and scatterplot3d (Ligges and Mächler 2003), if not already loaded, will too be loaded by this call.”
Solving Ordinary Differential Equations in R (2012, methodology): “This can easily be done using the R package scatterplot3d [17]. library(scatterplot3d)scatterplot3d(out[,-1], type = "l", lwd = 2, xlab = "", ylab = "", zlab = "", main = "rigidode")”
Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS (2012, background): “…normalized vectors, it only is able to take into account the direction of the vectors, which yields this unintuitive result (Herrmann 1992). and Maechler 2003), for three-dimensional scatter plots: R> library("scatterplot3d") R> scatterplot3d(patterns, pch =…”